metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: skin_decease
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9871794871794872
skin_decease
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0680
- Accuracy: 0.9872
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2359 | 0.8621 | 100 | 0.2427 | 0.9744 |
| 0.086 | 1.7241 | 200 | 0.1178 | 0.9872 |
| 0.0435 | 2.5862 | 300 | 0.0801 | 0.9872 |
| 0.0312 | 3.4483 | 400 | 0.0748 | 0.9872 |
| 0.023 | 4.3103 | 500 | 0.0715 | 0.9872 |
| 0.0197 | 5.1724 | 600 | 0.0696 | 0.9872 |
| 0.0174 | 6.0345 | 700 | 0.0687 | 0.9872 |
| 0.0161 | 6.8966 | 800 | 0.0684 | 0.9872 |
| 0.0151 | 7.7586 | 900 | 0.0680 | 0.9872 |
Framework versions
- Transformers 4.43.2
- Pytorch 2.2.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1